1 citations · 1 across the 4 of their papers we have counts for
4 papers
MusicMark: A Robust Generative Watermarking Framework for Music Generation
Seohwan Yun, Jeeyoung Yun, Yongjin Kim +2
AI music generation has rapidly advanced alongside commercial platforms, raising the need for reliable watermarking for provenance and attribution. However, existing audio watermar…
SGPO: Self-Generated Preference Optimization based on Self-Improver
Hyeonji Lee, Daejin Jo, Seohwan Yun +1
Large language models (LLMs), despite their extensive pretraining on diverse datasets, require effective alignment to human preferences for practical and reliable deployment. Conve…
EP-SAM: Weakly Supervised Histopathology Segmentation via Enhanced Prompt with Segment Anything
Joonhyeon Song, Seohwan Yun, Seongho Yoon +2
This work proposes a novel approach beyond supervised learning for effective pathological image analysis, addressing the challenge of limited robust labeled data. Pathological diag…
CAD: Memory Efficient Convolutional Adapter for Segment Anything
Joohyeok Kim, Joonhyeon Song, Seohwan Yun +2
The Foundation model for image segmentation, Segment Anything (SAM), has been actively researched in various fields since its proposal. Various researches have been proposed to ada…